Bibliographic record
Abstract
Al Rashid Mosque, Canada’s first and one of the earliest in North America, was erected in Edmonton in the depth of the Depression of the 1930s. Over time, the story of this first mosque, which served as a magnet for more Lebanese Muslim immigrants to Edmonton, was woven into the folklore of the local community. —Baha Abu-Laban, Foreword Edmonton’s Al Rashid Mosque has played a key role in Islam’s Canadian development. Founded by Muslims from Lebanon, it has grown into a vibrant community fully integrated into Canada’s cultural mosaic. The mosque continues to be a concrete expression of social good, a symbol of a proud Muslim Canadian identity. Al Rashid Mosque provides a welcome introduction to the ethics and values of homegrown Muslims. The book traces the mosque’s role in education and community leadership and celebrates the numerous contributions of Muslim Canadians in Edmonton and across Canada. Al Rashid Mosque is a timely and important volume of Islamic and Canadian history. "Forty years ago, as a young scholar in Islamic Studies at the University of Alberta, Al Rashid’s Muslims welcomed my queries, tolerated my ignorance, and joyfully opened their homes and their hearts." —Earle H. Waugh Earle H. Waugh has studied Islam in Canada and the Middle East for most of his adult life. He is Professor Emeritus at the University of Alberta and a senior scholar in the areas of religious studies, health and culture, and Indigenous language maintenance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.154 | 0.041 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".